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国内外岩浆岩数据库现状与应用前景
引用本文:张颖慧,王涛,焦守涛,郭磊,范润龙,王杨刚,张建军.国内外岩浆岩数据库现状与应用前景[J].高校地质学报,2020,26(1):11.
作者姓名:张颖慧  王涛  焦守涛  郭磊  范润龙  王杨刚  张建军
作者单位:1. 自然资源部深地动力学重点实验室,中国地质科学院地质研究所,北京100037;; 2. 北京离子探针中心,北京100037;; 3. 中国地质调查局发展研究中心,北京100037
摘    要:超过三分之二的地壳岩石是由来自深部的岩浆作用形成,岩浆岩记录的信息是深时数字地球(Deep-time Digital Earth,DDE)特别是深部过程研究的重要载体。岩浆岩分布范围广,样品众多,分析、定年相对方便和精确,易于数据累积。在过去的十多年,全球科学家建立了EarthChem、GEOROC、DataView等多个优秀的岩浆岩数据库。随着大数据时代的到来,地球科学也在经历向地球系统科学的重大转变。如何进一步整合分散在研究机构和个人手中的越来越多的数据,建立能服务大数据和人工智能方法的数据平台,推动地球科学研究由理论驱动的传统因果推理方法向数据驱动的大数据方法转变,是新的很有希望的突破点。文章系统介绍了目前国内外已有的岩浆岩相关数据库及其运行情况,为未来DDE计划整合全球海量岩浆岩数据,建设开放、共享、统一的大数据平台提供经验和基础。同时,也列举了以岩浆岩大数据驱动的科学研究的典型实例,并结合DDE相关任务,对利用岩浆岩大数据和人工智能进一步解决四维地球深部圈层物质构成、交换与动力学这一关键科学问题提出新的展望。


Review of Igneous Rock Databases and Their Application Prospect
ZHANG Yinghui,WANG Tao,JIAO Shoutao,GUO Lei,FAN Runlong,WANG Yanggang,ZHANG Jianjun.Review of Igneous Rock Databases and Their Application Prospect[J].Geological Journal of China Universities,2020,26(1):11.
Authors:ZHANG Yinghui  WANG Tao  JIAO Shoutao  GUO Lei  FAN Runlong  WANG Yanggang  ZHANG Jianjun
Institution:1. Key Laboratory of Deep-Earth Dynamics of Ministry of Natural Resources, Institute of Geology, Chinese Academy of; Geological Sciences, Beijing 100037, China;; 2. Beijing SHRIMP Center, Beijing 100037, China;; 3. Development Research Center of China Geological Survey, Beijing 100037, China
Abstract:More than two-thirds of the Earth crust rocks are formed by magmatism from the deep. The information recorded by igneous rocks are important resource for understanding deep process, as well as evolution of the Earth during deep-time, and therefore valuable for the Deep-time Digital Earth (DDE) Big Science Program. Igneous rocks are ideal candidates for data accumulation because of their wide distribution, significant amount and rather accurate dating. Over the past decade, scientists around the world have established excellent igneous rock databases such as EarthChem, GEOROC and DataView. All have their virtues and defects. Under the DDE project, to accumulate igneous rock data scattered in research institutions and individuals, and establish a highly integrated database along with a platform suited with artificial intelligence algorithms, will be a breakthrough point. They will promote the Earth science research from traditional theory-driven searching to big data-driven discovering. The current paper reviews the existing igneous rock databases, including their data, systems and operations, in order to provide reference for the future DDE igneous rock database. Several big data-driven researches on igneous rock during recent years have also been reviewed, to explore all aspects of future research when igneous rock big data is combined with AI technique.
Keywords:
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